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Artificial Intelligence and Machine Learning in 2D/3D Medical Image Processing
Loot Price: R1,557
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Artificial Intelligence and Machine Learning in 2D/3D Medical Image Processing
Expected to ship within 12 - 17 working days
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Digital images have several benefits, such as faster and
inexpensive processing cost, easy storage and communication,
immediate quality assessment, multiple copying while preserving
quality, swift and economical reproduction, and adaptable
manipulation. Digital medical images play a vital role in everyday
life. Medical imaging is the process of producing visible images of
inner structures of the body for scientific and medical study and
treatment as well as a view of the function of interior tissues.
This process pursues disorder identification and management.
Medical imaging in 2D and 3D includes many techniques and
operations such as image gaining, storage, presentation, and
communication. The 2D and 3D images can be processed in multiple
dimensions. Depending on the requirement of a specific problem, one
must identify various features of 2D or 3D images while applying
suitable algorithms. These image processing techniques began in the
1960s and were used in such fields as space, clinical purposes, the
arts, and television image improvement. In the 1970s, with the
development of computer systems, the cost of image processing was
reduced and processes became faster. In the 2000s, image processing
became quicker, inexpensive, and simpler. In the 2020s, image
processing has become a more accurate, more efficient, and
self-learning technology. This book highlights the framework of the
robust and novel methods for medical image processing techniques in
2D and 3D. The chapters explore existing and emerging image
challenges and opportunities in the medical field using various
medical image processing techniques. The book discusses real-time
applications for artificial intelligence and machine learning in
medical image processing. The authors also discuss implementation
strategies and future research directions for the design and
application requirements of these systems. This book will benefit
researchers in the medical image processing field as well as those
looking to promote the mutual understanding of researchers within
different disciplines that incorporate AI and machine learning.
FEATURES Highlights the framework of robust and novel methods for
medical image processing techniques Discusses implementation
strategies and future research directions for the design and
application requirements of medical imaging Examines real-time
application needs Explores existing and emerging image challenges
and opportunities in the medical field
General
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